> ## Documentation Index
> Fetch the complete documentation index at: https://docs.heyaskr.ai/llms.txt
> Use this file to discover all available pages before exploring further.
# Vision
> Why Askr exists, and where it's going.
## Our belief
AI is becoming the way people work, create and learn. It is moving from a novelty
you try occasionally to infrastructure you rely on daily, in the same way the
internet did. When something becomes that essential, how you access it matters as
much as the thing itself.
Right now, access is fragmenting. It is split across a dozen companies, each with
its own subscription, its own login, and its own walled garden. We think that's
backwards. **Access to every AI model should be open, neutral, and
pay as you go,** not locked behind five monthly bills, and not tied to whichever
single company you happened to subscribe to.
## The shift to AI native work
More and more work now starts with a model. People draft, design, plan, code and
research by asking an AI first and refining from there. As that becomes the
default, most people won't use a single model. They'll use the best one for each
task: one for careful reasoning, another for images, another for video, another
for quick everyday questions.
The tools haven't caught up with that reality. They still assume you pick one
provider and commit to it monthly. That made sense when AI was a single product.
It makes no sense when the best model for the job changes from task to task, and
from month to month.
## Why subscriptions are the wrong model
A subscription asks you to predict your usage in advance and pay a flat fee
whether you were right or not. For a fast-moving field, that has three problems.
* **You overpay.** Most people use a fraction of what they pay for, and still pay
the full fee in a quiet month.
* **You get locked in.** Committing to one provider means missing better models
that launch elsewhere, unless you stack another bill on top.
* **You lose visibility.** A flat fee hides what any single request actually
costs, so you can never really tell where the money goes.
Pay-per-use fixes all three. You pay for exactly what you run, you are free to
switch the moment something better appears, and every request carries a visible
price.
## Why a neutral layer matters
Askr is the **neutral layer that sits above all the models.** You're never locked
to one lab. When a better model launches, you use it the same day, from the same
balance, by changing one setting. No migration, no new subscription, no waiting
for your provider to catch up.
Neutrality is the point. A layer that doesn't favour any single model can always
route you to the best option, keep prices honest, and adopt new models as fast as
they arrive. Three principles guide everything we build:
Every model, one place. No lock-in to a single provider.
Pay only for what you use. No subscriptions, no waste.
Every cost is visible and itemised. Nothing hidden.
## Why crypto native
Money should move as freely as the AI does. AI is global and instant, but the way
we pay for it usually isn't: it depends on cards, banks and borders. Crypto lets
anyone, anywhere fund an Askr balance, privately, instantly, without a bank or a
card in the middle. It's the payment layer that matches an open, global product.
Funding in crypto also fits the pay-per-use model. You top up when you want, in
any amount, and draw it down request by request. We hold the balance in USDT so
it stays steady in value, giving you the openness of crypto with the predictability
of a dollar-denominated balance.
## Where this goes
Our aim is simple: make every AI model available to anyone, from one balance, at
a fair price, funded in a way that works everywhere. As models multiply and
improve, the value of a neutral layer that keeps up with all of them only grows.
That is what we're building toward.
This page describes our direction. It will grow as Askr does.